Hire PyTorch developers

The salary of a PyTorch developer is around $151K per/yr according to Indeed in the US. But wages can range between $127K and $204K depending on the seniority level of the specialist. Check the developers available on the Lemon.io platform, where you will only have to pay for hours worked by the chosen rate of the programmer, thus making the process of cooperation transparent and aligned for each party!

According to the Python Developers Survey 2023, PyTorch is used by 17% of Python developers. NumPy, pandas, and Matplotlib remain the most popular frameworks for data science tasks. PyTorch improved its position by 7 percentage points since 2022, probably as a result of the growing popularity of deep learning.

PyTorch was developed at Meta AI, formerly Facebook AI Research. It began as an internship project by Adam Paszke, advised and supervised by the key developer of the original Torch, Soumith Chintala. Later, 2 other core engineers Sam Gross and Gregory Chanan joined to development team. Nowadays, PyTorch is an open-source project and part of the umbrella of the Linux Foundation.

No, it’s free because PyTorch is open-source. So, that means PyTorch is free to use it in any commercial project, without spending a single dollar for licensing fees. Still, training a deep learning model with PyTorch can come at a cost. For example, cloud computing services paid for model training; or quite powerful hardware like GPUs or TPUs to purchase or rent.

Yes, OpenAI uses PyTorch for many of its machine-learning models and research projects. Some of the primary reasons PyTorch has become a favorite among many in the development of OpenAI advanced models are flexibility, ease of usability, and extensive community support. While OpenAI may also use other tools or frameworks where necessary, PyTorch will be a key component in their development process.

Yes, PyTorch is essentially for deep learning. Indeed, it’s a flexible and powerful platform to build and train neural networks based on dynamic computation graphs, automatic differentiation, and rich neural network building blocks. There are libraries like Torchvision for image processing, or Torchtext for NLP, with which rich ecosystems have been made available in PyTorch, as well as support for GPU-based acceleration, important for large model training. Due to the large community and a bunch of optimization algorithms supporting it, this model gains popularity in the tasks of Computer Vision, Natural Language Processing, and Reinforcement Learning.

Yes, you can assess a PyTorch developer’s abilities during the trial phase. We provide a risk-free paid evaluation period for new clients – up to 20 hours, enabling you to evaluate the developer’s performance on assignments before committing to a subscription.

In case of underperformance and if the developer does not meet expectations, we will introduce you to another remote developer under our guarantee of risk-free replacement.

Yes, PyTorch is in high demand, primarily in the fields of artificial intelligence and machine learning. The popularity of PyTorch stems from several reasons: it offers a flexible and intuitive framework for building and training deep learning models, is widely adopted in academic research and industrial applications, and provides efficient GPU support.

You can hire a PyTorch developer through Lemon.io in 48 hours. Before you hire the PyTorch developer from Lemon.io, we will manually check the relevant PyTorch developers from our community and show you candidates who are perfectly chosen for your project. The candidates who have already joined our community are pre-vetted: our recruiters have already checked their CVs, conducted screening calls and tech interviews with them, and they are ready to proceed with a final interview directly for your project.

To hire a PyTorch developer, requirements for the project need to be defined first — a list of necessary skills and experience stated. A detailed job description will include what you are looking for, responsibilities, qualifications, and an overview of your company. Creating a job posting on several different platforms like LinkedIn, Glassdoor, Indeed, Dice, specialized tech job boards, and developer communities allows you to find a fitting candidate. Screen their resume and portfolio for relevant experience. Then, follow up with technical and behavioral interviews, including coding challenges and code reviews. Check professional references for work history and abilities. Design a competitive offer of the grade of pay, benefits, etc., followed by easy onboarding with proper orientation and training. Look out for candidates who fit into your team’s culture and project needs.

Lemon.io, on the other hand, makes the process much simpler for you: you only need to proceed with 3 steps: discovery call, checking the 2-3 CVs of the pre-screened PyTorch Engineers manually selected for you from the huge developer community, and connecting with the right engineer.